I have always been
fascinated with weather. One of the most interesting aspects of
weather is rainfall, and its variance from one place to another.
When mountains are nearby, the rainfall amounts can vary
significantly within a small distance. One place this happens
frequently is in the San Francisco bay area, especially in the
southern end of the Santa Clara Valley.

There are two basic
effects on precipitation caused by mountains. There is the
"orographic" effect and the "rain shadow"
effect (See Fig. 1). The orographic effect happens on the
windward side of a mountain. The rainfall amounts increase
dramatically as you move farther up the mountain on the windward
side. The orographic effect is why Kentfield, in Marin County can
receive 1300mm of rain per year while San Francisco only 500mm.

The other effect is
the rain shadow effect. Since I live on the leeward side of a
mountain, I am more interested in the rain shadow effect. The
rain shadow effect is where precipitation amounts drop
significantly on the leeward side of a mountain. This is why
places like Arica, Chile average only .5mm of rain per year. The
Andes Mountains, to the east, receive a lot of precipitation, but
it is all gone by the time it gets to the Atacama Desert. The
same thing happens in the Santa Clara Valley, although on a
smaller scale.

I have been
charting the weather at my house for about the last five years. I
have also paid very close attention to weather statistics from
the Internet, television and newspapers. Regarding the San Jose
area, I have noticed that the southern end receives more rainfall
than in the north. My house in the far southern end typically
receives 30%-100% more rainfall than downtown San Jose. This is
very interesting, since both places are in the same valley, and
relatively close to each other. The Santa Cruz Mountains, to the
south, can receive more than four times as much. Because of this,
the South Bay is a perfect place to study the rain shadow effect.

One problem in
studying the rain shadow effect is that information on this topic
is very difficult to obtain. I have an entire bookshelf full of
weather books, and none of them have more than a glossary
definition. Most of them do not even mention the rain shadow
effect. I searched a few libraries and book stores, but could
find little more than a definition or brief explanation. I was
also interested in detailed information on exactly how the
mountains affect the rainfall in different parts of this valley.
I could not find any detailed information on the subject.

Here are a few
things that I would like to try to prove in my experiment.

HYPOTHESIS

Since the rain
shadow effect is so complex, there are several parts to my
hypothesis.

Because of
wind, rainfall that is intensified by orographic lifting does
not stop at the edge of a mountain. This is what causes there
to be more rainfall at the southern end of the Santa Clara
Valley than in the middle and northern end. (See Fig. 2)

As the
intensified rain from the mountains passes into the valley,
it loses its intensity at a constant rate. This rate is
mainly dependent on temperature, upper-level wind speed, and
the vertical height of the clouds.

There is a
point where rainfall amounts no longer vary depending on the
distance from the mountains (mountains in the direction the
wind is coming from).

The distance
from this point to the mountains depends on the temperature,
wind speed and the vertical height of the clouds.

An equation
could be made to estimate the ratio of the amount of rainfall
before orographic lifting takes place to the amount of
rainfall in the rain shadow.

OTHER
QUESTIONS I WOULD LIKE TO ANSWER REGARDING RAIN

How far is rain
blown on its way to the ground? (See Fig. 3)

Could the rain
at Location 3 be coming from above the mountains?

MATERIALS
AND METHODS

The hardest part of
this experiment was obtaining the data. I needed very specific
information. I needed several rain gauges, equally spaced, and
oriented in the right direction. I looked though various books
and the Internet, but could not find anything useful to me.
Because detailed, highly specific information for such a small
geographic location is nearly impossible to find, I had to
retrieve the data myself.

I bought 7 high
quality Sunbeam rain gauges. (Fig. 4)

I studied a
topographical map and determined the ideal locations to place
them. (See Fig. 4.5)

I used my
altimeter, along with the topographic map to find the
elevation at these different sites. (See Table 1)

I set up the 7
rain gauges. A few were placed in peoples backyards,
one at an apartment complex, one at a church, one on top of a
park sign, and one at my house. I had to ask for permission
to set up most of them. (See Fig. 4.5 for a map of the
locations)

A large storm
arrived the evening after I set up the rain gauges.

After the rain
had stopped, I checked all of the rain gauges, made sure none
of them were stolen, recorded the data, and emptied them.

I recorded
additional data from about 25 automated rain gauges located
all over Santa Cruz and Santa Clara counties. Three of those
were also used for the first part of the experiment.

I repeated this
for the next two systems, which came soon after the first
one.

RESULTS

The data was
gathered from three storms (See Table 1). Two were very strong
systems with a lot of wind and rain. The third had light winds
and little rain. For each storm, I plotted the amount of rain in
millimeters vs. the SSW to NNE distance in kilometers from the
ridge of the 800 meter tall Sierra Azul Mountains.

(Refer to Table 1
and Fig. 5) For the first storm, the graph started downward at
what looked like a constant slope. Then at about 17km it leveled
off. There appeared to be a straight horizontal line from 17km to
39km. The mean slope of the graph from 0km to 17km was about
2.7mm(rain) per km(distance). The average temperature for the
storm at Location 3, 6km NNE of the reference point, was about
13ºC. The peak winds during the
storm at Location 3 were from the south at 15.2m/s.

The second storm
came shortly after the first. The average temperature again was
about 13ºC. The peak winds were from the south at
11.6m/s. The graph was somewhat different. The point where it
leveled off was around 12km. The slope from 0km to 12km was about
-3.6mm/km.

The third storm was
different from the first two. The wind at the surface was calm
for most of the time it was raining. The highest winds were only
about 4m/s from the west. The average temperature during the time
it was raining was 12ºC. There did not seem to be
any kind of constant slope. Note - Rainfall amounts were so
light that any pattern was most likely nothing more than an
anomaly, and probably of no use to this experiment, but all data
should at least be mentioned.

DISCUSSION

Precipitation is
formed or intensified by air rising, cooling below the dew point,
and condensing. The opposite is true as air descends. It is dried
out and precipitation loses some of its intensity. Mountains
force air to rise and fall. Simply stated, the rain shadow effect
is caused by air warming up and losing its moisture after it
passes over mountains.

Wind is the main
variable. Without wind, there would be no rain shadow effect.
There are two major effects of wind. First of all, the wind
pushes the air against the mountains, causing it to rise and then
fall on the other side, which means more precipitation in the
mountains and less in the valleys. If that is the only effect the
wind has, the rain patterns should be fairly uniform, and
proportional with different storms of different magnitudes. There
is, however, a second effect the wind has. Tall clouds, enhanced
by orographic lifting, are pushed forward by the wind carrying
with them some of the heavier rain that would normally fall in
the mountains. Once they get over the mountains, they begin to
dry out and lose some of their intensity. If all the other
factors, such as wind speed, temperature, air pressure, air
instability, and humidity are about the same, and they usually
are in the valley during a winter storm, the rainfall should
decrease in intensity at a constant rate. Newtons First Law
states that an object (such as a cloud) with no force acting on
it moves with constant velocity. There is no force (besides a
very small amount of wind resistance) acting on a cloud in the
opposite direction the wind is blowing. Therefore, clouds will
move at a constant velocity in the direction the wind is blowing.
If precipitation is moving at a constant velocity and losing its
intensity at a constant rate, the amount of rainfall from the
mountains toward the valley will decrease at a constant rate.
That is the basis for my main hypothesis, and it seems to be
substantially reflected by the data.

There is also a
limit to the rain intensity that is lost as it moves into the
valley. In most storms, there is still plenty of moisture in the
valley for rain, just not enough to maintain the added
precipitation due to orographic lifting. Because of this, there
should be very little variation in rainfall past the reach of the
intensified rain forced in to the valley by wind. This hypothesis
is also substantially reflected by the data.

(Please refer to
Fig. 5 for the graphs) The first two storms showed a definite
pattern, and seemed to confirm the hypotheses. The rainfall
patterns both consisted of two main parts. The first part was
sloped and the second was flat. The initial sloped line
represents the transition from the mountains to the valley. That
slope is dependent on the wind speed, and also on the height of
the clouds. For higher winds, the line should have less of a
slope because the effects are spread (blown) over a larger area.
Weak winds should have steep slopes because the same effects are
spread over a smaller area. When there is very light wind, the
line should be very sloped, but since the rain shadow effect is
minimal, the line would be very short. When there is no wind,
there is no initial sloped line because rainfall should be equal
on both sides.

Just as expected,
the windier storm had a smaller slope than the storm with less
wind. Also, taller clouds should travel farther before
dissipating, so taller clouds would also produce a smaller slope.
This was not much of a factor in these two particular storms,
since the rainfall intensity (which should be proportional to the
cloud height) was nearly equal in both systems.

Both of the initial
lines are slightly curved. Since there are an infinite number of
different wind speeds and cloud heights in a storm, there are an
infinite number of slopes for the initial line. The addition of
an infinite number of straight lines with different slopes
produces a curve. Storms usually do not have the same wind speeds
and cloud heights for equal time periods, so the shape of the
curve is totally dependent on what percentage of the storm is at
a certain intensity. More rain usually falls when there is more
wind, so the curve should remain somewhat straight.

In the first storm.
There is was steeper slope at the beginning, and it became less
pronounced shortly thereafter. That was because that particular
storm had two major parts. There was a period of heavy winds and
heavy rain, which would produce a flat slope. There was also
another long period of the storm with heavy rain and light winds.
The steep slope which would represent that period, added with the
flatter part, would produce an initially steep line which becomes
less sloped where the effects of the lighter winds taper off. The
rainfall vs. distance graph represents that very well.

The second storm
had a fairly constant wind speed throughout the entire storm,
which should produce a very straight graph. This proved to be
what happened.

There is also a
horizontal region on both graphs. The horizontal region
represents the area unaffected by wind-blown rain and clouds.
Since wind is no longer a major factor here, and the other
variables (mainly temperature and humidity) are not significant
enough, this area should be represented by a straight line.
However, that does not mean that there is no rainfall variation
past a certain point. It means that since the expected variables
are too insignificant, the rainfall in this location is random
and unpredictable. It depends on the particular storm, and the
particular cells and bands that happen to develop. The rainfall
in this area should not usually vary much. One exception might be
during scattered thunderstorm activity where temperature,
instability, and chance play a major role.

Just as expected,
the graphs of both storms leveled off to nearly a straight
horizontal line in the area farthest away from the mountains. The
point at which the sloped part of the graph and the flat part
meet should also be dependent on the wind speed and cloud
heights, and it appears to be according to the graphs. The
winds effects are carried farther with higher wind speeds,
and with bigger clouds there is more to carry, so they should not
dissipate as soon. The horizontal part of the graph should begin
at a farther distance in a windier storm. Just as expected, the
horizontal part of the graph of the windier storm began at a
greater distance than in the other storm. So far, the first four
parts to the hypothesis appear to have been sound assumptions.

It should be
possible to make an equation to approximate the amount of
rainfall at a given distance from the ridge of the mountains.
However, I have no way of measuring some of the variables needed
for such an equation. Some of the things I needed to know during
each minute of the storm were the heights of the clouds, the
upper-level wind speed, the lifted index (the stability of the
air), the dew point at different altitudes, the temperature at
different altitudes, and any other variables I may have
overlooked. These values are impractical and difficult for anyone
to measure accurately, even with the most sophisticated
equipment. The rainfall variation in even the most contrasting
storms is still relatively small compared to the amount of
possible error. Even my best guess at these values would be so
inaccurate that the derived equation would be practically
useless. I can, however, make an equation to predict a less
complex aspect of the rain shadow effect.

Although some is
added by orographic lifting, the rainfall that was originally
destined for the Santa Clara Valley also decreases after it
passes over the mountains. The result is less rainfall in San
Jose than on the other side of the Santa Cruz Mountains.
Scotts Valley is located on the other side of the mountains
in the direction the rain usually comes from. Although
Scotts Valley was too far away for me to set up rain
gauges, I did have access to their automated rainfall data via
the Internet. I can use the data from the first two storms, along
with the fact that there should be no difference in rainfall
amounts when there is no wind and consequently no rain shadow
effect, to make an equation to determine the ratio of rainfall
between one side of the mountains and the rain shadow side. Since
the rain shadow effect is almost entirely based on the wind
speed, the wind speed is the only variable I need for a good
approximation. By plotting the three points, I found the equation. The value
for rain sub San Jose is at the Civic Center downtown. I chose
this location because it is beyond the reach of wind-blown
orographic clouds and rain. W is the peak wind speed at Location
3, 8m above the ground, 6km NNE of the Sierra Azul ridge. This is
a poor value to use for wind speed, but it is the best I had. It
should suffice, since it is close to being proportional to the
average wind speeds aloft. It assumes that more rain falls when
there is more wind, and the wind aloft is not extremely variable.
Temperature should play a small role in this equation, but was
not included because of insufficient data. Since air can hold
more moisture when it is warmer, there would probably be a
smaller difference between both sides when the temperature is
higher, but that is a whole new experiment. Also, since San Jose
and Scotts Valley are 35 kilometers away from each other, a
lot of random things can happen between the two places. Other
variables besides wind and possibly temperature are too
insignificant compared to the random variations that are
possible.

It should be
mentioned that not all storms are like the ones I studied. Some
storms come from different directions. The purpose of this
experiment was to investigate typical winter storms that come in
from the west with southerly or south-southwesterly winds. These
are by far the most common in this area. Although the numbers
only apply to these types of storms, the concepts apply to every
storm.

CONCLUSION

After doing this
experiment, I am much more confident about my original theories.
The results seemed to substantiate my hypotheses. The rain shadow
equation seems to work, but I need more data and more
opportunities to test it. Since I find the data so interesting, I
will continue this experiment.